Recent field observations demonstrate that a significant discrepancy exists between models and measurements of large dust aerosol particles at remote sites. We assess the fraction of this bias explained by assumptions involving four different dust production processes. These include dust source size distribution (constant or dynamically changing according to saltation and sandblasting theory), wind speed distributions (using mean wind or a probability density function (PDF)), parent soil aggregate size distribution, and the discretization (number of bins) in the dust size distribution. The Dust Entrainment and Deposition global model is used to simulate the measurements from the Puerto Rican Dust Experiment (PRIDE) (2000). Using wind speed PDFs from observed National Centers for Environmental Prediction winds results in small changes in downwind size distribution for the production which neglects sandblasting, but it results in significant changes when production includes sandblasting. Saltation-sandblasting generally produces more large dust particles than schemes which neglect sandblasting. Parent soil aggregate size distribution is an important factor when calculating size-distributed dust emissions. Changing from a soil with large grains to a soil with smaller grains increases by 50% the fraction of large aerosols (D >5 μm) modeled at Puerto Rico. Assuming that the coarse medium sand typical of West Africa dominates all source regions produces the best agreement with PRIDE observations.

We investigate the influence of mineral dust on tropospheric chemistry in the present climate at the global scale. The analysis examines the effects of dust on photolysis and heterogeneous uptake, operating independently and together. In numerical experiments the size-resolved, time-varying mineral dust distribution predicted by the global Dust Entrainment and Deposition (DEAD) model perturbs the gas phase species in a global chemical transport model (University of California at Irvine (UCI) CTM). We find that the photolysis perturbation dominates limited regions in the low to middle troposphere, while heterogeneous uptake dominates the rest of atmosphere. Coupling of the photochemical and heterogeneous effects of dust is weak in the global mean but moderate in dusty regions, where coupling is sometimes responsible for more than 20% of local O₃ changes. Ozone and odd-nitrogen concentrations are perturbed in opposite directions by photolysis and heterogeneous chemistry, resulting in a weak net change. However, both processes decrease the concentrations of OH and HO₂. The global mean change due to dust is −0.7% for tropospheric O₃, −11.1% for OH, −5.2% for HO₂, and −3.5% for HNO₃. Large seasonal signals are present near dust source regions. Over the North African region and tropical Atlantic Ocean downwind, OH decreases by −66.8%, six times more than the global mean reduction. Interestingly, net photolysis-induced annual mean O₃ changes are greater in the Southern Hemisphere than in the Northern Hemisphere, where significantly more dust and O₃ precursors reside. In polar regions, O₃ change is dominated by transported O₃ and is not sensitive to local dust concentration. O₃ change due to photolysis depends not only on dust vertical structure but also on the availability of O₃ precursors. O₃ change due to heterogeneous reactions on dust is sensitive to dust vertical structure, mainly through the influence of temperature on uptake rates.

An accurate cost model that accounts for dataset size and structure can help optimize geoscience data analysis. We develop and apply a computational model to estimate data analysis costs for arithmetic operations on gridded datasets typical of satellite- or climate model-origin. For these dataset geometries our model predicts data reduction scalings that agree with measurements of widely used geoscience data processing software, the netCDF Operators (NCO). I/O performance and library design dominate throughput for simple analysis (e.g. dataset differencing). Dataset structure can reduce analysis throughput ten-fold relative to same-sized unstructured datasets. We demonstrate algorithmic optimizations which substantially increase throughput for more complex, arithmetic-dominated analysis such as weighted-averaging of multi-dimensional data. These scaling properties can help to estimate costs of distribution strategies for data reduction in cluster and grid environments.

 Variations in the Arctic Oscillation (AO) and its regional manifestation, the North Atlantic Oscillation (NAO), generate much of the nonseasonal variability in the winter climate over the Northern Hemisphere midlatitudes. Despite being an internal mode of the atmosphere, the Arctic and North Atlantic Oscillations (N/AO) exhibit a slightly red spectrum, varying on quasi-biennial (2–3 years) and quasi-decadal time scales. Such low-frequency variability is likely due to the coupling of the atmosphere to boundary conditions and/or external forcings. Here we show that Eurasian snow cover, particularly over eastern Siberia (ESB), exhibits quasi-biennial persistence similar to the N/AO. Furthermore, the snow-AO mechanism operates on quasi-biennial timescales, with fall ESB snow cover significantly related to vertically propagating Rossby wave activity and the N/AO for the next two to three winters. On the basis of land surface model simulations from the Global Land Data Assimilation System (GLDAS), the interseasonal carryover of ESB snow is related to soil moisture anomalies and an evaporation-convection feedback. These findings suggest quasi-biennial persistence of the N/AO is partly due to land surface forcing in the form of both ESB snow and soil moisture anomalies.

The NCAR CAM3 GCM with prescribed, satellite-based snow albedo (SA) is used to investigate the remote effects of snow cover on Northern Hemisphere (NH) winter climate. A pair of 100 ensemble member experiments are integrated through the autumn-winter season, with prescribed high and low SA over Eurasia (EA). Similar to other non-CAM GCM studies using prescribed snow mass, anomalous EA snow albedo produces a wave activity pulse that propagates into the stratosphere, culminating in a negative phase Arctic Oscillation– (AO-) like surface response. This occurs for idealized but representative SA anomalies, as well as for more realistic SA anomalies. Similar experiments over North America (NA) and the entire NH are also performed. Unlike prior studies, anomalous NA snow yields a significant AO signal. Here, the local NA surface cooling elicits a transient eddy response, which propagates downstream to Eurasia, resulting in significant but short-lived cooling and upward propagating wave activity over Siberia. A negative AO-like response develops, primarily confined to the stratosphere/upper troposphere, which eventually gives way to a tropospheric AO-like response of the opposite phase, due to equatorward wave refraction and wave divergence. Reanalysis data support this NA snow-positive AO response. Snow forcing experiments for the whole NH, however, yield a weakened AO signal. This is due to a muted wavenumber-1 and -2 response caused by destructive interference between the background stationary wave and the corresponding Rossby wave response, which results in negligible wave activity reaching the stratosphere.

Coccidioidomycosis (Valley Fever) is a fungal infection found in the southwestern United States, northern Mexico, and some places in Central and South America. The fungi that cause it (Coccidioides immitis and Coccidioides posadasii) are normally soil dwelling, but, if disturbed, become airborne and infect the host when their spores are inhaled. It is thus natural to surmise that weather conditions, which foster the growth and dispersal of Coccidioides, must have an effect on the number of cases in the endemic areas. This article reviews our attempts to date at quantifying this relationship in Kern County, California (where C. immitisis endemic). We have examined the effect on incidence resulting from precipitation, surface temperature, and wind speed. We have performed our studies by means of a simple linear correlation analysis, and by a generalized autoregressive moving average model. Our first analysis suggests that linear correlations between climatic parameters and incidence are weak; our second analysis indicates that incidence can be predicted largely by considering only the previous history of incidence in the county—the inclusion of climate- or weather-related time sequences improves the model only to a relatively minor extent. Our work therefore suggests that incidence fluctuations (about a seasonally varying background value) are related to biological and/or anthropogenic reasons, and not so much to weather or climate anomalies.

Variations in the Arctic Oscillation (AO) and its regional manifestation, the North Atlantic Oscillation (NAO), generate much of the nonseasonal variability in the winter climate over the Northern Hemisphere midlatitudes. Despite being an internal mode of the atmosphere, the Arctic and North Atlantic Oscillations (N/AO) exhibit a slightly red spectrum, varying on quasi-biennial (2-3 years) and quasi-decadal time scales. Such low-frequency variability is likely due to the coupling of the atmosphere to boundary conditions and/or external forcings. Here we show that Eurasian snow cover, particularly over eastern Siberia (ESB), exhibits quasi-biennial persistence similar to the N/AO. Furthermore, the snow-AO mechanism operates on quasi-biennial timescales, with fall ESB snow cover significantly related to vertically propagating Rossby wave activity and the N/AO for the next two to three winters. On the basis of land surface model simulations from the Global Land Data Assimilation System (GLDAS), the interseasonal carryover of ESB snow is related to soil moisture anomalies and an evaporation-convection feedback. These findings suggest quasi-biennial persistence of the N/AO is partly due to land surface forcing in the form of both ESB snow and soil moisture anomalies.

 Solar absorption decays exponentially with depth in snowpacks. However, most climate models constrain all snowpack absorption to occur uniformly in the top-most snow layer. We show that 20–45% of solar absorption by deep snowpacks occurs more than 2 cm beneath the surface. Accounting for vertically-resolved solar heating alters steady-state snow mass without changing bulk snow albedo, and ice-albedo feedback amplifies this effect. Vertically-resolved snowpack heating reduces winter snow mass on the Tibetan Plateau by 80% in one GCM, and significantly increases 2 m air temperature. These changes significantly reduce model-measurement discrepancies. Our results demonstrate that snowpack radiative heating plays a significant role in regulating surface climate and hydrology. More accurate snowpack radiation has the potential to improve predictions of related climate processes, such as spring runoff and the Asian Monsoon.

The dominant process in producing fine dust aerosols during saltation is thought to be sandblasting. Recent studies claim that due to competing physical processes, emission efficiencies of dust aerosols oscillate with increasing wind friction speed. These oscillations can result in order of magnitude changes in dust mass emissions. Our work shows that emission efficiencies, and hence emissions of dust aerosols are smooth functions of the wind friction speed for natural soil size distributions. This rules out oscillations as an explanation for scatter in experimental data. We show and explain the reasons for the oscillations.